The generation of natural language descriptions from structured data has been one of the key goals of NLG. Existing systems for such tasks may be either rule based or data driven. Rule based systems often require large amounts of manual effort to design specific rules for each domain of data and are typically not scalable across domains where the vocabulary and schema of the structures of the domains vary considerably. Data driven systems often require parallel data, e.g., data containing pairs, which may be elusive.